19 research outputs found
Prediction of Customer Movements in Large Tourism Industries by the Means of Process Mining
Customer movements in large tourism industries (such as public transport systems, attraction parks or ski resorts) can be understood as business processes. Their processes describe the flow of persons through the networked systems, while Information Systems log the different steps. The prediction of how large numbers of customers will behave in the near future is a complex and yet unsolved challenge. However, the possible business benefits of predictive analytics in the tourism industry are manifold. We propose to approach this task with the yet unexploited appli-cation of predictive process mining. In a prototypical use case, we work together with two major European ski resorts. We implement a predictive process mining algorithm towards the goal of predicting near future lift arrivals of skiers within the ski resort in real-time. Furthermore, we present the results of our prototypical implementation and draw conclusions for future research in the area
TRUST MANAGEMENT â AN INFORMATION SYSTEMS PERSPECTIVE
The focus of the Information Systems (IS) research on trust has been on the perception of trust and explaining the concept in terms of its antecedents. The merits of this descriptive and explanatory knowledge notwithstanding, the usefulness and applicability of this knowledge for organizations that aim at actively influencing their trust position is limited. In light of recent public scandals in areas such as social media, car manufacturing or financial services, organizations require an understanding of how customer trust can be managed using contemporary information systems solutions. In this paper we propose trust management as an IS theme of increasing relevance and draw upon extant research in IS, psychology, and marketing to bridge the gap between topics such as risk management, compliance management and governance on the one hand and trust management on the other. We utilize Botsmanâs concept of uncertainty as a proxy for customer trust to bring together organizational approaches that can objectively reduce uncertainty linked to an organization, its processes, products, and services with the customerâs perception of this uncertainty. We contribute to the further maturity of trust management by providing new foundations and providing explicit advice on how to improve trust in organizations
HELP IS ON THE WAY â PROVIDING USER SUPPORT FOR EPC MODELLING VIA A SYSTEMATIC PROCEDURE MODEL
Process models and consequently business process modelling languages get more and more complex. This is especially true for the event-driven process chain (EPC), since the absence of a clearly defined standard renders EPC modelling difficult. On top, modelling itself is no trivial task. To address this issue, several frameworks and guidelines have emerged to support process modelling. However, most of them remain at a generic level. Currently, there is no user support with respect to the actual modelling process that is specific to the EPC language. To address these needs, the paper applies a design-oriented research approach and proposes a systematic procedure model specifically tailored towards EPC mod-elling as current outcome of this research in progress. We argue that the procedure model facilitates the modelling process and thus has the potential to increase model quality
Live Query - Visualized Process Analysis
Business process management (BPM) becomes continuously challenging through a steadily increasing number and even more complex processes. For enabling an effective and efficient control of business processes, (semi-)automatic approaches are necessary as a supporting means. However, these approaches are often hardly applicable in practice since they lack a broad applicability or an acceptable ease of use. This work aims to close this gap by providing an approach that supports a widely applicable, (semi-)automatic analysis of business process models and makes the analysis comprehensible using a graphical visualization
A framework for human microbiome research
A variety of microbial communities and their genes (the microbiome) exist throughout the human body, with fundamental roles in human health and disease. The National Institutes of Health (NIH)-funded Human Microbiome Project Consortium has established a population-scale framework to develop metagenomic protocols, resulting in a broad range of quality-controlled resources and data including standardized methods for creating, processing and interpreting distinct types of high-throughput metagenomic data available to the scientific community. Here we present resources from a population of 242 healthy adults sampled at 15 or 18 body sites up to three times, which have generated 5,177 microbial taxonomic profiles from 16S ribosomal RNA genes and over 3.5 terabases of metagenomic sequence so far. In parallel, approximately 800 reference strains isolated from the human body have been sequenced. Collectively, these data represent the largest resource describing the abundance and variety of the human microbiome, while providing a framework for current and future studies
Structure, function and diversity of the healthy human microbiome
Author Posting. © The Authors, 2012. This article is posted here by permission of Nature Publishing Group. The definitive version was published in Nature 486 (2012): 207-214, doi:10.1038/nature11234.Studies of the human microbiome have revealed that even healthy individuals differ remarkably in the microbes that occupy habitats such as the gut, skin and vagina. Much of this diversity remains unexplained, although diet, environment, host genetics and early microbial exposure have all been implicated. Accordingly, to characterize the ecology of human-associated microbial communities, the Human Microbiome Project has analysed the largest cohort and set of distinct, clinically relevant body habitats so far. We found the diversity and abundance of each habitatâs signature microbes to vary widely even among healthy subjects, with strong niche specialization both within and among individuals. The project encountered an estimated 81â99% of the genera, enzyme families and community configurations occupied by the healthy Western microbiome. Metagenomic carriage of metabolic pathways was stable among individuals despite variation in community structure, and ethnic/racial background proved to be one of the strongest associations of both pathways and microbes with clinical metadata. These results thus delineate the range of structural and functional configurations normal in the microbial communities of a healthy population, enabling future characterization of the epidemiology, ecology and translational applications of the human microbiome.This research was supported in
part by National Institutes of Health grants U54HG004969 to B.W.B.; U54HG003273
to R.A.G.; U54HG004973 to R.A.G., S.K.H. and J.F.P.; U54HG003067 to E.S.Lander;
U54AI084844 to K.E.N.; N01AI30071 to R.L.Strausberg; U54HG004968 to G.M.W.;
U01HG004866 to O.R.W.; U54HG003079 to R.K.W.; R01HG005969 to C.H.;
R01HG004872 to R.K.; R01HG004885 to M.P.; R01HG005975 to P.D.S.;
R01HG004908 to Y.Y.; R01HG004900 to M.K.Cho and P. Sankar; R01HG005171 to
D.E.H.; R01HG004853 to A.L.M.; R01HG004856 to R.R.; R01HG004877 to R.R.S. and
R.F.; R01HG005172 to P. Spicer.; R01HG004857 to M.P.; R01HG004906 to T.M.S.;
R21HG005811 to E.A.V.; M.J.B. was supported by UH2AR057506; G.A.B. was
supported by UH2AI083263 and UH3AI083263 (G.A.B., C. N. Cornelissen, L. K. Eaves
and J. F. Strauss); S.M.H. was supported by UH3DK083993 (V. B. Young, E. B. Chang,
F. Meyer, T. M. S., M. L. Sogin, J. M. Tiedje); K.P.R. was supported by UH2DK083990 (J.
V.); J.A.S. and H.H.K. were supported by UH2AR057504 and UH3AR057504 (J.A.S.);
DP2OD001500 to K.M.A.; N01HG62088 to the Coriell Institute for Medical Research;
U01DE016937 to F.E.D.; S.K.H. was supported by RC1DE0202098 and
R01DE021574 (S.K.H. and H. Li); J.I. was supported by R21CA139193 (J.I. and
D. S. Michaud); K.P.L. was supported by P30DE020751 (D. J. Smith); Army Research
Office grant W911NF-11-1-0473 to C.H.; National Science Foundation grants NSF
DBI-1053486 to C.H. and NSF IIS-0812111 to M.P.; The Office of Science of the US
Department of Energy under Contract No. DE-AC02-05CH11231 for P.S. C.; LANL
Laboratory-Directed Research and Development grant 20100034DR and the US
Defense Threat Reduction Agency grants B104153I and B084531I to P.S.C.; Research
Foundation - Flanders (FWO) grant to K.F. and J.Raes; R.K. is an HHMI Early Career
Scientist; Gordon&BettyMoore Foundation funding and institutional funding fromthe
J. David Gladstone Institutes to K.S.P.; A.M.S. was supported by fellowships provided by
the Rackham Graduate School and the NIH Molecular Mechanisms in Microbial
Pathogenesis Training Grant T32AI007528; a Crohnâs and Colitis Foundation of
Canada Grant in Aid of Research to E.A.V.; 2010 IBM Faculty Award to K.C.W.; analysis
of the HMPdata was performed using National Energy Research Scientific Computing
resources, the BluBioU Computational Resource at Rice University
Common variants at ABCA7, MS4A6A/MS4A4E, EPHA1, CD33 and CD2AP are associated with Alzheimer's disease
We sought to identify new susceptibility loci for Alzheimer's disease through a staged association study (GERAD+) and by testing suggestive loci reported by the Alzheimer's Disease Genetic Consortium (ADGC) in a companion paper. We undertook a combined analysis of four genome-wide association datasets (stage 1) and identified ten newly associated variants with P †1 Ă 10â5. We tested these variants for association in an independent sample (stage 2). Three SNPs at two loci replicated and showed evidence for association in a further sample (stage 3). Meta-analyses of all data provided compelling evidence that ABCA7 (rs3764650, meta P = 4.5 Ă 10â17; including ADGC data, meta P = 5.0 Ă 10â21) and the MS4A gene cluster (rs610932, meta P = 1.8 Ă 10â14; including ADGC data, meta P = 1.2 Ă 10â16) are new Alzheimer's disease susceptibility loci. We also found independent evidence for association for three loci reported by the ADGC, which, when combined, showed genome-wide significance: CD2AP (GERAD+, P = 8.0 Ă 10â4; including ADGC data, meta P = 8.6 Ă 10â9), CD33 (GERAD+, P = 2.2 Ă 10â4; including ADGC data, meta P = 1.6 Ă 10â9) and EPHA1 (GERAD+, P = 3.4 Ă 10â4; including ADGC data, meta P = 6.0 Ă 10â10)
FROM LEGISLATION TO POTENTIAL COMPLIANCE VIOLATIONS IN BUSINESS PROCESSES â SIMPLICITY MATTERS
The compliance of businesses is a highly relevant topic for companies of all sectors. Compliance comprises all necessities for obeying legal regulations as well as mandatory norms, and violations can entail painful penalties. Since nearly all companies base their daily business on the execution of business processes (consciously or unconsciously), these business processes also have to be compliant. Hence, as part of business process management, business process compliance becomes increasingly important for companies. However, the checking of business processes for their compliance is â against the backdrop of many existing business processes and incessantly changing regulations â not an easy task. Several research approaches have been developed for supporting compliance checking. A common way is to examine the models of the business processes automatically to detect compliance violations with predefined patterns that represent possible violations. Unfortunately, only the fewest approaches are actually applied by companies due to high technical restrictions or difficult handling. The presented graph-theoretic approach strives to overcome this with a high level of simplicity and the applicability to real-world process models. For that, a real legislative passage is gradually transformed into an automatically searchable compliance pattern and applied to real process models